IDEAS home Printed from https://ideas.repec.org/a/ids/ijisde/v18y2024i5-6p669-685.html
   My bibliography  Save this article

Research on sustainable development, innovation and entrepreneurship transformation needs of key energy industries

Author

Listed:
  • Liang Tang

Abstract

In order to improve the sustainable development ability of the energy industry, the artificial intelligence algorithm is introduced into the sustainable development prediction, the sustainable development evaluation model of L-M improved BP neural network is proposed, and the grey prediction model is used to predict the transformation demand. The algorithm simulation shows that the fitting degree between the L-M improved BP neural network and the expected value of experts in the evaluation of sustainable development has reached 0.98. In addition, the prediction performance test of the grey prediction model shows that its prediction accuracy has reached 99.4%. The above results show that it is effective to use L-M improved BP neural network to evaluate the sustainable development of the energy industry, which can help the energy industry understand the current development status.

Suggested Citation

  • Liang Tang, 2024. "Research on sustainable development, innovation and entrepreneurship transformation needs of key energy industries," International Journal of Innovation and Sustainable Development, Inderscience Enterprises Ltd, vol. 18(5/6), pages 669-685.
  • Handle: RePEc:ids:ijisde:v:18:y:2024:i:5/6:p:669-685
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=140843
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:ijisde:v:18:y:2024:i:5/6:p:669-685. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=33 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.